Details
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Task
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Status: Resolved
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Major
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Resolution: Fixed
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None
Description
For tables with many chunks (2M+ rows, 20k+ chunks), `pyarrow.Table.take` will be around 1000x slower compared to the `pyarrow.Table.take` on the table with combined chunks (1 chunk). Unfortunately, if such table contains large list data type, it's easy for the flattened table to contain more than 2**31 rows and serialization of the table with combined chunks (eg for Plasma store) will fail due to `pyarrow.lib.ArrowCapacityError: Cannot write arrays larger than 2^31 - 1 in length`
I couldn't find a way to enable 64bit support for the serialization as called from Python (IpcWriteOptions in Python does not expose the CIpcWriteOptions 64 bit setting; further the Python serialization APIs do not allow specification of IpcWriteOptions)
I was able to serialize successfully after changing the default and rebuilding
modified cpp/src/arrow/ipc/options.h @@ -42,7 +42,7 @@ struct ARROW_EXPORT IpcWriteOptions { /// \brief If true, allow field lengths that don't fit in a signed 32-bit int. /// /// Some implementations may not be able to parse streams created with this option. - bool allow_64bit = false; + bool allow_64bit = true; /// \brief The maximum permitted schema nesting depth. int max_recursion_depth = kMaxNestingDepth;
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